
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))


# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "54"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder


# Use environment variables to figure out path to the csvs and auto_metrics
antenna = os.environ["ANTENNA"]
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "128"
csv_folder = "/home/obs/src/H5C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H5C_Notebooks/auto_metrics_inspect"


display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))


import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna


# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, '*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 102 csvs in /home/obs/src/H5C_Notebooks/_rtp_summary_
Found 98 auto_metrics notebooks in /home/obs/src/H5C_Notebooks/auto_metrics_inspect


# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H5C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H5C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'


this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        antnum = row['Ant']
        if antnum != int(antenna):
            continue
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break


# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])


display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))


html_to_display = ''
for am_html in auto_metric_htmls:
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line: 
            break


HTML(html_to_display)

JDs	A Priori Status	Auto Metrics Flags	Dead Fraction in Ant Metrics (Jee)	Dead Fraction in Ant Metrics (Jnn)	Crossed Fraction in Ant Metrics	Flag Fraction Before Redcal	Flagged By Redcal chi^2 Fraction	ee Shape Modified Z-Score	nn Shape Modified Z-Score	ee Power Modified Z-Score	nn Power Modified Z-Score	ee Temporal Variability Modified Z-Score	nn Temporal Variability Modified Z-Score	ee Temporal Discontinuties Modified Z-Score	nn Temporal Discontinuties Modified Z-Score	Average Dead Ant Metric (Jee)	Average Dead Ant Metric (Jnn)	Average Crossed Ant Metric	Median chi^2 Per Antenna (Jee)	Median chi^2 Per Antenna (Jnn)
2459594	digital_ok	0.00%	0.00%	0.00%	0.00%	1.08%	0.00%	0.371088	-0.845720	-0.674624	-0.793652	-0.820235	0.965035	-1.392956	-0.818728	0.7624	0.7813	0.2592	2.714741	2.992518
2459593	digital_ok	0.00%	0.00%	0.00%	0.00%	2.15%	0.00%	-0.433886	0.429280	0.317720	-0.573180	-0.294447	0.665882	-1.295937	-1.038852	0.6944	0.6893	0.2478	2.086230	2.161078
2459592	digital_ok	0.00%	100.00%	100.00%	0.00%	-	-	0.633786	-0.727570	0.030386	-0.772832	-0.488709	1.108418	-1.937590	-0.051649	0.0339	0.0562	0.0020	nan	nan
2459591	digital_ok	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	350.120201	350.375088	inf	inf	74.779245	77.643014	868.390169	903.065040	nan	nan	nan	0.000000	0.000000
2459590	digital_ok	0.00%	0.00%	0.00%	0.00%	1.62%	0.00%	-0.470726	1.019240	0.023469	-0.866452	0.015426	1.447847	-1.302472	-0.427928	0.6328	0.6387	0.3469	1.823114	1.810021
2459589	digital_ok	0.00%	0.00%	0.00%	0.00%	2.69%	0.00%	-0.605123	0.364280	-0.487791	-1.008624	-0.717899	-0.332281	-1.062519	-0.972136	0.6800	0.6767	0.2778	1.720820	1.803398
2459588	digital_ok	0.00%	0.00%	0.00%	0.00%	2.69%	0.00%	0.237397	0.333973	0.627915	-0.184084	-1.047469	0.249120	-1.117266	-0.934300	0.7274	0.7102	0.2340	2.435641	2.101533
2459587	digital_ok	100.00%	-	-	-	100.00%	0.00%	-0.807769	1.475000	2.053443	-0.549217	2.077618	3.812276	1.760215	2.282885	nan	nan	nan	13.062984	13.354840
2459586	digital_ok	0.00%	0.00%	0.00%	0.00%	2.70%	0.00%	-1.592614	-0.440896	-0.714541	-0.070270	-0.197661	-1.101733	-1.193177	-1.052391	0.6368	0.6449	0.3311	1.585489	1.562234
2459585	digital_ok	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	0.258624	0.688963	-0.898233	-0.242871	-0.718244	-0.601871	-1.272789	-0.418699	0.0364	0.0601	0.0025	0.000000	0.000000
2459584	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-1.507941	0.991066	1.530726	4.600235	10.183760	9.082081	-0.772637	-0.796047	0.5825	0.5924	0.3454	12.114671	11.078220
2459583	digital_ok	0.00%	0.00%	0.00%	0.00%	3.23%	0.54%	-1.722709	0.497835	1.101689	2.159639	0.426149	-0.240156	-1.045783	-0.940012	0.6363	0.6457	0.3626	1.774659	1.753373
2459582	digital_ok	0.00%	0.00%	0.00%	0.00%	2.70%	0.54%	-1.497019	0.684669	1.245291	2.081900	0.334159	-0.519438	-1.042861	-0.912833	0.6443	0.6507	0.3656	1.728254	1.700380
2459581	digital_ok	0.00%	0.00%	0.00%	0.00%	3.24%	0.54%	-1.581557	0.263396	0.530043	2.675507	0.168123	0.119753	-0.904942	-0.996555	0.6369	0.6460	0.3741	1.304842	1.353979
2459580	digital_ok	0.00%	0.00%	0.00%	0.00%	3.76%	0.54%	-1.335530	0.585033	1.428137	2.852906	1.016861	0.021563	-1.282332	-0.749832	0.6474	0.6537	0.3630	1.699900	1.639696
2459579	digital_ok	0.00%	0.00%	0.00%	0.00%	3.76%	0.00%	-1.309828	0.477852	1.796263	3.158922	0.488589	-0.093096	-0.971208	-1.069894	0.6420	0.6491	0.3706	1.817221	1.737399
2459578	digital_ok	0.00%	100.00%	100.00%	0.00%	-	-	0.291142	1.456244	-0.323592	1.108401	-0.015034	1.894047	-0.587565	-0.998513	0.0404	0.0723	0.0037	nan	nan
2459577	digital_ok	0.00%	0.00%	0.00%	0.00%	3.78%	0.00%	-1.556805	0.403931	0.607538	2.563503	0.229926	0.272815	-1.007316	-0.911075	0.6371	0.6458	0.3713	1.329197	1.389272
2459576	digital_ok	0.00%	0.00%	0.00%	0.00%	4.30%	0.00%	-1.212577	0.114935	0.271324	1.796054	-0.049315	0.620030	-0.699265	-0.941569	0.6674	0.6755	0.3668	1.555207	1.546863
2459575	digital_ok	0.00%	0.00%	0.00%	0.00%	4.30%	0.00%	-1.299011	0.164554	0.491311	1.409980	0.030483	-0.735608	0.163263	0.820669	0.7370	0.7402	0.3169	1.534759	1.596112
2459574	digital_ok	0.00%	0.00%	0.00%	0.00%	3.78%	0.00%	-1.428984	-0.032388	0.210052	1.362791	-0.174458	0.273331	-1.079831	-1.038939	0.6646	0.6734	0.3690	1.616566	1.615642
2459573	digital_ok	0.00%	0.00%	0.00%	0.00%	3.78%	0.00%	-1.117029	-0.065437	1.836525	3.468536	0.426299	-0.234917	-0.993817	-0.888018	0.6586	0.6704	0.3713	1.607986	1.657374
2459572	digital_ok	0.00%	0.00%	0.00%	0.00%	3.78%	0.00%	-1.532328	-0.223182	0.435464	1.683609	0.192384	-0.114725	-0.772007	-1.183076	0.6612	0.6711	0.3674	1.271519	1.344010
2459571	digital_ok	100.00%	100.00%	100.00%	0.00%	-	-	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	nan	nan
2459570	digital_ok	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459569	digital_ok	0.00%	0.00%	0.00%	0.00%	4.32%	0.00%	-1.089306	0.514792	0.409804	1.968246	-0.282665	1.247905	-0.245350	1.209427	0.7484	0.7536	0.2298	2.072185	2.041967
2459566	digital_ok	0.00%	0.00%	0.00%	0.00%	4.32%	0.00%	-1.238359	0.292831	0.882432	2.290457	0.144365	0.182166	-1.055258	-0.342233	0.6590	0.6665	0.3766	1.623997	1.621634
2459565	digital_ok	0.00%	-	-	-	100.00%	0.00%	1.059218	1.059218	0.968690	0.968690	-0.627210	-0.627210	-0.758470	-0.758470	nan	nan	nan	0.000000	0.000000
2459564	digital_ok	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	2841.899343	1332.277128	inf	inf	-54745.641104	-24964.880515	-93147.810753	-43297.665053	nan	nan	nan	0.000000	0.000000
2459563	digital_ok	0.00%	0.00%	0.00%	0.00%	5.38%	0.00%	-1.668574	0.307899	-0.770306	1.899202	-0.308822	0.106067	-0.810033	-0.499757	0.6644	0.6714	0.3703	1.630179	1.622686
2459562	digital_ok	0.00%	0.00%	0.00%	0.00%	4.86%	0.00%	-1.140474	-0.997386	-1.182747	-1.919400	-0.874506	-0.506310	-0.419328	-0.549627	0.6665	0.6754	0.3679	1.700570	1.618976
2459561	digital_ok	0.00%	0.00%	0.00%	0.00%	4.86%	0.00%	-1.315489	-0.280717	-1.400611	-1.900076	-0.989073	-0.154881	-0.812553	-0.647809	0.6703	0.6810	0.3727	1.641028	1.616420
2459560	digital_ok	0.00%	0.00%	0.00%	0.00%	4.86%	0.00%	-1.011761	-0.714853	-1.191298	-1.989108	-0.577977	0.191069	-0.453218	-0.800427	0.6654	0.6728	0.3796	1.761796	1.607889
2459559	digital_ok	0.00%	0.00%	0.00%	0.00%	5.38%	2.15%	-1.451946	-0.585203	-1.310835	-2.297426	-0.854813	0.036222	-0.422785	-0.599175	0.6671	0.6729	0.3662	1.747045	1.635055
2459558	digital_ok	0.00%	0.00%	0.00%	0.00%	5.38%	0.00%	-1.271326	0.604601	1.670951	2.380964	0.822900	-0.439517	-1.072077	-0.804817	0.6695	0.6743	0.3738	1.500214	1.484554
2459557	digital_ok	-	100.00%	100.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.0381	0.0735	0.0032	nan	nan
2459556	digital_ok	0.00%	0.00%	0.00%	0.00%	4.86%	0.00%	-1.135470	0.295917	1.589825	2.595443	0.337307	0.320256	-1.594379	-0.545094	0.6622	0.6684	0.3757	1.629234	1.640611
2459554	digital_ok	-	0.00%	0.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.6725	0.6785	0.3817	nan	nan
2459553	digital_ok	-	0.00%	0.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.6694	0.6755	0.3799	nan	nan
2459552	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.989429	0.564232	1.925428	4.819516	1.350848	1.384575	-0.751897	-0.387133	0.6741	0.6798	0.3794	9.846113	9.654618
2459551	digital_ok	0.00%	0.00%	0.00%	0.00%	5.38%	0.00%	-1.195757	-0.703385	-1.491730	-2.503567	-1.103045	-0.663052	-0.439419	-0.465869	0.6627	0.6725	0.3762	1.626802	1.505940
2459550	digital_ok	-	99.18%	99.18%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.0407	0.0565	0.0028	nan	nan
2459549	digital_ok	0.00%	0.00%	0.00%	0.00%	4.86%	0.00%	-1.133721	0.255519	1.173825	2.830976	0.392049	0.664102	-1.006430	-0.674738	0.6666	0.6778	0.3840	1.534018	1.550055
2459542	digital_ok	0.00%	0.00%	0.00%	0.00%	22.32%	0.00%	-1.373027	0.260356	-0.229702	3.793145	1.429208	0.130250	-0.933890	-1.158869	0.7333	0.7385	0.3363	1.340682	1.368692
2459541	digital_ok	0.00%	1.34%	1.34%	0.00%	21.88%	0.00%	-0.976006	0.465106	1.780946	3.900004	0.433714	3.074539	-0.357779	0.899469	0.7245	0.7262	0.3179	1.598204	1.553710
2459540	digital_ok	0.00%	0.00%	0.00%	0.00%	21.88%	1.79%	-1.450012	0.621645	-1.634731	-1.872244	-1.000311	-0.578629	-1.071590	-1.004138	0.7328	0.7286	0.3302	1.556555	1.509168
2459536	digital_ok	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	-1.818123	0.720955	2.244678	6.272095	0.953672	3.482968	-0.789590	-1.547532	0.0869	0.0809	0.0120	0.000000	0.000000
2459535	digital_ok	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	-1.240078	0.194246	-1.360358	-1.718249	-0.960964	-0.852924	-0.673560	-0.774748	0.0832	0.0816	0.0116	45.757267	38.582546
2459534	digital_ok	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	-1.210682	-0.052718	-1.331290	-1.592862	-0.194384	-0.452511	-0.472120	-0.829909	0.0934	0.0869	0.0124	13.193440	5.773223
2459533	digital_ok	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	-1.136907	1.299535	1.755017	2.655576	0.057093	1.204316	-1.115383	-0.739393	0.0887	0.0809	0.0119	0.000000	0.000000
2459532	digital_ok	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	-1.185369	1.013550	2.328079	3.687299	0.667020	1.729826	-1.184679	-0.925001	0.0871	0.0797	0.0117	0.000000	0.000000
2459530	digital_ok	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	-1.257440	0.280882	-1.211407	-1.791950	-0.751601	-0.841322	-0.381080	-0.758887	0.0916	0.0879	0.0159	53.656108	53.278277
2459527	digital_ok	0.00%	-	-	-	100.00%	0.00%	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459524	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.324533	1.465112	1.910155	2.749754	2.478666	5.905963	-1.253830	-0.707796	0.9143	0.9412	0.2689	0.000000	0.000000
2459523	digital_ok	100.00%	-	-	-	100.00%	0.00%	-0.885276	2.111338	1.769637	4.842252	-0.743914	4.645160	-1.042001	-1.090013	nan	nan	nan	21.054132	11.666841
2459522	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.434051	2.513432	2.086824	4.298692	1.210888	2.663511	-0.952790	1.472267	0.6698	0.7198	0.3506	0.000000	0.000000
2459513	digital_ok	0.00%	100.00%	100.00%	0.00%	-	-	0.689441	1.471115	-0.412996	0.415034	0.415613	2.564462	-0.699345	-0.704359	0.0472	0.0670	0.0042	nan	nan
2459508	digital_ok	0.00%	0.00%	0.00%	0.00%	81.58%	0.00%	-0.663564	1.489025	1.422471	1.271528	0.010506	0.702197	0.645413	1.121605	0.9173	0.9579	0.1655	0.000000	0.000000
2459505	digital_ok	0.00%	0.00%	0.00%	0.00%	0.00%	0.00%	-0.942881	1.452875	1.867184	3.097010	-0.505809	0.781726	-0.941301	-1.006143	0.8973	0.8755	0.1791	5.433864	4.968624
2459503	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.207632	1.778025	2.219052	3.625486	2.919173	6.523628	-1.338032	-1.159905	0.8740	0.8685	0.4230	0.000000	0.000000
2459501	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.418283	1.187044	2.541640	2.962942	0.942573	5.422832	-1.109413	-1.157109	0.8781	0.9116	0.3507	0.000000	0.000000
2459500	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	2.691851	2.669214	3.805376	3.436620	4.895319	5.174067	-1.327854	-0.997412	0.8855	0.9070	0.3446	0.000000	0.000000
2459499	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	2.591065	3.183302	4.316371	4.186380	4.773961	5.124584	-1.149653	0.858753	0.8920	0.9441	0.1647	0.000000	0.000000
2459498	digital_ok	0.00%	0.00%	0.00%	0.00%	94.74%	0.00%	0.956339	1.673432	2.186400	2.568570	2.089171	3.132401	-1.322408	-1.150477	0.8926	0.9089	0.3724	0.000000	0.000000
2459497	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.276048	2.191941	2.484193	2.998880	2.954024	4.825517	-1.146690	-0.871109	0.9013	0.9339	0.3147	0.000000	0.000000
2459496	digital_ok	0.00%	0.00%	0.00%	0.00%	94.74%	0.00%	0.754924	1.693891	1.987022	2.492198	1.924600	3.608737	-1.282058	-1.023324	0.9211	0.9272	0.3402	0.000000	0.000000
2459495	digital_ok	0.00%	0.00%	0.00%	0.00%	94.74%	0.00%	0.552627	1.433804	1.743335	2.387332	1.463476	3.252111	-1.174189	-0.946551	0.9174	0.9235	0.3691	0.000000	0.000000
2459494	digital_ok	0.00%	0.00%	0.00%	0.00%	94.74%	0.00%	1.050657	1.419831	2.174813	2.233237	1.669801	2.689695	-1.106526	-1.276784	0.9074	0.9158	0.3803	0.000000	0.000000
2459492	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-1.655821	1.049368	2.665428	5.878670	0.586264	6.357825	-0.782031	0.815398	0.7702	0.8176	0.3244	5.990874	4.892413
2459491	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-1.817481	0.292202	2.631066	6.300542	1.780640	8.346630	-1.215980	0.188126	0.8041	0.8298	0.2683	4.187613	3.060703
2459490	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-1.462977	1.104784	2.456713	7.211510	0.977120	6.011465	14.709410	0.833834	0.7582	0.8106	0.3795	6.906916	5.049373
2459489	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-1.523766	0.535212	2.348536	6.031423	-0.473808	6.387791	-0.457827	-0.755689	0.7741	0.8158	0.3277	7.970630	5.070641
2459488	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-1.405608	0.423413	2.253286	5.247328	-0.790291	6.444021	-0.769158	-1.745824	0.7757	0.8188	0.3532	0.000000	0.000000

Antenna Season Report Notebook¶

Antenna 128 Report

Load relevant info from summary CSVs¶

Table 1: Per-Night RTP Summary Info For This Atenna¶

Antenna 128, Node 10:

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

Antenna 128: 2459626

Antenna 128: 2459625

Antenna 128: 2459624

Antenna 128: 2459623

Antenna 128: 2459622

Antenna 128: 2459621

Antenna 128: 2459620

Antenna 128: 2459619

Antenna 128: 2459618

Antenna 128: 2459617

Antenna 128: 2459616

Antenna 128: 2459615

Antenna 128: 2459614

Antenna 128: 2459613

Antenna 128: 2459612

Antenna 128: 2459611

Antenna 128: 2459610

Antenna 128: 2459609

Antenna 128: 2459608

Antenna 128: 2459607

Antenna 128: 2459605

Antenna 128: 2459604

Antenna 128: 2459603

Antenna 128: 2459602

Antenna 128: 2459598

Antenna 128: 2459597

Antenna 128: 2459596

Antenna 128: 2459595

Antenna 128: 2459594

Antenna 128: 2459593

Antenna 128: 2459592

Antenna 128: 2459591

Antenna 128: 2459590

Antenna 128: 2459589

Antenna 128: 2459588

Antenna 128: 2459587

Antenna 128: 2459586

Antenna 128: 2459585

Antenna 128: 2459584

Antenna 128: 2459583

Antenna 128: 2459582

Antenna 128: 2459581

Antenna 128: 2459580

Antenna 128: 2459579

Antenna 128: 2459578

Antenna 128: 2459577

Antenna 128: 2459576

Antenna 128: 2459575

Antenna 128: 2459574

Antenna 128: 2459573

Antenna 128: 2459572

Antenna 128: 2459571

Antenna 128: 2459570

Antenna 128: 2459569

Antenna 128: 2459566

Antenna 128: 2459565

Antenna 128: 2459564

Antenna 128: 2459563

Antenna 128: 2459562

Antenna 128: 2459561

Antenna 128: 2459560

Antenna 128: 2459559

Antenna 128: 2459558

Antenna 128: 2459556

Antenna 128: 2459552

Antenna 128: 2459551

Antenna 128: 2459549

Antenna 128: 2459542

Antenna 128: 2459541

Antenna 128: 2459540

Antenna 128: 2459536

Antenna 128: 2459535

Antenna 128: 2459534

Load antenna metric spectra and waterfalls from `auto_metrics` notebooks.¶